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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Incident Command workspace showing the question, observations, and next decision.
DevOps
Incident Command
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.During an acute incident with several people involved, the method creates a clear leadership and communication structure. It reduces chaos when fast coordination and clean situational awareness are both needed at once.DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report.
Complexitydifferent
HighMediumMediumLow
Timedifferent
1-4 Wochen30-90 minAs needed1-2 h
Participantsdifferent
6-30 Experten1-64-152-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption ListIncident Log, Action Tracker, Stakeholder UpdatesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
IncidentOperationsReliability
StrategyDecisionAssumptionsHypothesis
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